Journal of Trace Elements in Medicine and Biology 31 (2015) 78–84
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NUTRITION
Association of plasma manganese levels with chronic renal failure Cristina Sánchez-González a , Carlos López-Chaves a , Jorge Gómez-Aracena b , Pilar Galindo c , Pilar Aranda a , Juan Llopis a,∗ a b c
Department of Physiology, Campus Cartuja, University of Granada, E-18071 Granada, Spain Department of Preventive Medicine and Public Health, University of Malaga, E-29071 Malaga, Spain Department of Nephrology, Virgen de las Nieves University Hospital, E-18014 Granada. Spain
a r t i c l e
i n f o
Article history: Received 20 November 2014 Accepted 7 April 2015 Keywords: Manganese Chronic renal failure Gender BMI
a b s t r a c t Manganese (Mn) is an essential trace element involved in the formation of bone and in amino acid, lipid and carbohydrate metabolism. Mn excess may be neurotoxic to humans, affecting specific areas of the central nervous system. However, relatively little is known about its physiological and/or toxicological effects, and very few data are available concerning the role of Mn in chronic renal failure (CRF). This paper describes a 12-month study of the evolution of plasma Mn levels in predialysis patients with CRF and the relationship with energy and macronutrient intake. The participants in this trial were 64 patients with CRF in predialysis and 62 healthy controls. Plasma levels of creatinine, urea, uric acid, total protein and Mn were measured. The glomerular filtration rate (GFR) was calculated using the Cockcroft-Gault index. The CRF patients had higher plasma levels of creatinine, urea, uric acid and Mn and a lower GFR than the controls. Plasma Mn was positively correlated with creatinine, plasma urea and plasma uric acid and was negatively correlated with the GFR and the intake of energy and macronutrients. In conclusion, CRF in predialysis patients is associated with increases in circulating levels of Mn. © 2015 Elsevier GmbH. All rights reserved.
Introduction Alterations in trace element metabolism in renal insufficiency are common. Nevertheless, the mechanisms responsible for these changes are still not fully understood [1,2]. Manganese (Mn) is an essential trace element involved in the formation of bone and in amino acid, lipid and carbohydrate metabolism. However, Mn excess may be neurotoxic to humans, affecting specific areas of the central nervous system [3,4]. Little information exists regarding the behaviour of Mn in renal disease and what has been reported is contradictory and mainly focused on haemodialysis patients. Some authors have observed significant increases in Mn content in the hair of patients [5]. Ohtake et al. [6] reported a case of Mn-induced Parkinsonism in a patient on maintenance haemodialysis therapy. According to another study, the occurrence of bilateral pallidal hyperintensity on T1-weighted images in all patients undergoing haemodialysis is associated with high serum Mn levels [7]. However, other authors have described the opposite effect. Some authors have measured a decrease in Mn
∗ Corresponding author. Tel.: +34 958241000x20320/626797356; fax: +34 958 248959. E-mail address: [email protected] (J. Llopis). http://dx.doi.org/10.1016/j.jtemb.2015.04.001 0946-672X/© 2015 Elsevier GmbH. All rights reserved.
levels in haemodialysis patients [8–10]. Koh et al. [11] observed an association between low Mn values in blood and the risk of renal disease, and suggested that this situation may favour disease progression. This element is a cofactor for SOD, so Mn deficiency may contribute to excess oxidative stress in uraemia [12–14]. Given the limited information available on the role of Mn in chronic renal failure (CRF), the aim of this study is to investigate changes in plasma levels of Mn in predialysis patients with CRF and their relation to the biochemical parameters used in monitoring these patients and to the intake of energy and macronutrients.
Materials and methods Patients The participants in this cross-sectional trial were patients with CRF in predialysis who attended the nephrology outpatient clinic of the Virgen de las Nieves University Hospital, Granada (Spain). The following inclusion criteria were applied: plasma creatinine concentration >2.5 mg/dL, plasma creatinine clearance between 10 and 45 mL/min, stable clinical condition (stable blood pressure; no special diet; no digestive system or systemic disease, neoplasias or treatment with corticosteroids or immunosuppressors), normalised metabolic acidosis and lipid alterations, age between 18
C. Sánchez-González et al. / Journal of Trace Elements in Medicine and Biology 31 (2015) 78–84
and 70 years. This study was carried out in accordance with the World Medical Association Code of Ethics (Declaration of Helsinki) and all procedures were approved by the Hospital’s Ethics Committee. The study group comprised 64 patients (27 women, 37 men) aged 18–70 years with a mean age of 54 ± 16 years (mean ± SD). Control samples were obtained at random from adults aged 18–70 years living in Granada (Spain). Control participants were asked whether they had any acute or chronic illness and were included if they were (or appeared to be) in good health; pregnant and lactating subjects were excluded. The controls included 62 healthy people (33 men and 29 women) with a mean age of 46 ± 10 years. All participants provided their consent by signing an informed consent form. On day 0, all participants, and at the end of the study, only patients received a physical examination and clinical as well as nutritional data were recorded. The experimental phase of our study lasted 12 months, during which period the patients consumed the low-protein diets recommended by the hospital. Patients aged younger than 60 years and non-obese patients consumed a diet that provided 35 kcal/kg b.wt./day. Patients with obesity and/or older than 60 years were advised to consume a diet that provided 30 kcal/kg b.wt./day. To adjust the energy content of the low-protein diet, we considered obesity to exist when the participant weighed more than 125% of ideal weight [15]. After 12 months, the participation rate was 76.5%. The reasons for dropout or withdrawal included scheduled dialysis, death, laboratory error or loss of samples. The pharmacological treatment was similar for all patients and was adjusted depending on the individual’s clinical status. Medications included calcium-chelated phosphate, calcitriol, oral sodium bicarbonate, ferrous sulphate, antihypertensives (mainly angiotensin-converting enzyme inhibitors), furosemide and subcutaneous erythropoietin. At the beginning of the study and after 12 months, food consumption was assessed by a 24-h recall method that was repeated over 3 days (including a weekend or holiday) [16]. Data were obtained by a dietician with the aid of an open questionnaire and photographs as a reference for portion size. The pictures displayed fresh foods or foods prepared according to standard recipes for dishes that are widely consumed in the study area. Food intake was converted to energy and nutrients using the Spanish Food Composition Table [17]. The food composition database utilised AYS44 diet analysis software obtained from ASDE, SA (Valencia, Spain). Body weight was measured with a portable digital scale (Tefal, Sensitive Computer 9202 series 2/0, France) with a precision of 0.1 kg, and height was measured with a portable stadiometer (Holtain Portable, London, UK) with a precision of 0.1 cm. All measurements were obtained following the techniques and recommendations of the International Biological Programme by personnel suitably trained for this task. Analytical methods In the morning, blood was collected (10 mL) during fasting conditions in tubes that contained lithium heparin as an anticoagulant (Venoject, Terumo Corporation, Leuven, Belgium). The samples were centrifuged at 1200 × g for 15 min at 20 ◦ C to separate the plasma and were stored at −80 ◦ C until analysis. Excreted urine over a 24-h period was collected, following standard guidelines. Diuresis was measured and an aliquot stored at −80 ◦ C until analysis. Creatinine in plasma and 24-h urine, as well as the urea, uric acid and total protein concentrations in plasma were measured with enzymatic colorimetric tests in a Hitachi Modular P autoanalyser (Roche Diagnostics, Grenzach, Germany). The glomerular filtration rate (GFR) was estimated in patients by creatinine clearance
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and by the determination of diuresis and plasma and urinary creatinine at 24 h. The GFR was also measured in the patients and controls using the Cockcroft-Gault index = (140 − age/72 × plasma creatinine) × weight (×0.85 for women) [18]. Plasma Mn was determined using an inductively coupled plasma mass spectrometer (ICP-MS) model 7500 supplied by Agilent Technologies (Agilent, Tokyo, Japan), using a carrier gas flow of 1.03 L/min, collision gas (He) flow of 4.3 mL/min, RF power of 1550 W and energy discrimination of 3 V. All lenses were optimised daily. All materials used in the analysis were previously cleaned with supra-pure nitric acid and ultra-pure water (18.2 ) obtained using a Milli Q system. Samples and the certified reference material (Seronorm Trace Elements Serum L-1, Ref 201405. Billingstad, Norway) were prepared by attack with nitric acid and hydrogen peroxide (supra-pure quality, Merck) in a microwave digester (Milestone, Sorisole, Italy). When the samples had been digested, the extracts were collected and made up to a final volume of 10 mL with-ultra pure water for subsequent analysis. The calibration curve was prepared following the Ga addition technique (adding 0.04 mg/L) as an internal standard, using stock solutions of 1000 mg/L of Mn (Merck). The accuracy of the method was evaluated by analysis of the certified reference material, obtaining the value of 8.2 ± 0.2 g/L (certified value 7.8–8.8 g/L), and by recovery studies in samples of organs enriched with Mn standards, obtaining a recovery of 93%. The mean of five separate determinations was used. Statistical analysis All variables and indexes were analysed by descriptive statistics. Results are reported as means and standard deviations. When the data were distributed normally according to the Kolmogorov–Smirnov test, parametric tests (Student’s t-test for independent or related samples) were used. For variables that required nonparametric testing, the Mann–Whitney test for unrelated samples was used. Linear regression analysis was used to obtain bivariate correlations. Pearson’s correlation coefficient was calculated for the 95% confidence levels. All analyses were conducted with version 15.0 of the Statistical Package for Social Sciences (SPSS Inc., Chicago, IL). Differences were considered significant at the 5% probability level. Results This paper examines the 12-month evolution of plasma Mn levels in predialysis patients with CRF and the relationship with energy and macronutrient intake. Table 1 lists the following characteristics of the participants, showing mean values and SD for controls and patients at day 0 and for patients after 12 months: age, anthropometric variables (weight, height, body mass index [BMI]), plasma parameters indicative of renal function (plasma creatinine, Cockcroft-Gault index, plasma urea, plasma uric acid and plasma total proteins), plasma Mn and energy and macronutrient intake. All these parameters, except total plasma proteins, worsened significantly in the patients compared to controls during the study period, which is indicative of progressive renal dysfunction. Interestingly, patients with CRF had higher plasma Mn levels than the controls at the beginning of the study and these concentrations had increased significantly by the end of the study. In this study, we also evaluated the relationship between plasma levels of Mn and macronutrient consumption. This relationship had not been studied previously due to the unreliability of the food composition tables, as the number of foods in which Mn is present is very low. In our study, the female patients had a lower consumption
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Table 1 Characteristics of the participants. Controls, N = 62 Age (years) Weight (kg) BMI (kg/m2 )
46 ± 10 73 ± 13 27 ± 3
Biochemical parameters Plasma creatinine (mg/dL) Glomerular filtration rate (mL/min/1.73 m2 ) Cockcroft-Gault index Plasma urea (mg/dL) Plasma uric acid (mg/dL) Plasma total protein (g/dL) Plasma Mn (g/L)
0.68 ± – 116 ± 30 ± 4.8 ± 6.8 ± 0.65 ±
0.11
Energy and macronutrient intakes Energy (Mj/day) Protein (g/day) Energy from protein (%) Total fat (g/day) Energy from total fat (%) Saturated fat (g/day) Monounsaturated fat (g/day) Polyunsaturated fat (g/day) Carbohydrates (g/day) Energy from carbohydrates (%) Cholesterol (mg/day) Fibre (g/day)
10 92 16 104 39 30 52 14 264 42 349 18
± ± ± ± ± ± ± ± ± ± ± ±
Patients, N = 64 (Day 0) 54 ± 16a 76 ± 16 28 ± 6
Patients, N = 49 (12 months) 55 ± 16a 75 ± 16 27 ± 6
22 5 2.1 0.6 0.26
3.1 27 26 111 7.0 7.0 1.92
± ± ± ± ± ± ±
0.8a 9 9a 31a 1.9a 0.3 0.40a
3.7 25 24 123 7.5 7.2 2.90
± ± ± ± ± ± ±
1.0a 14 8a 41a 1.6a 0.5 0.86a , b
4 36 4 57 8 20 24 7 113 8 213 9
7.5 75 17 72 37 16 41 10 209 48 263 17
± ± ± ± ± ± ± ± ± ± ± ±
2a 22a 3 26a 7 7a 13a 3 63a 6a 119a 8
7.7 63 13 79 39 17 44 10 218 48 240 15
± ± ± ± ± ± ± ± ± ± ± ±
2a 14a 5a , b 21a 7 10a 12 6 46 8 160a 6
Values are expressed as the means ± SD. a Patients vs. controls. b Patients at day 0 vs. patients at 12 months. P < 0.05.
of energy, protein, fat, carbohydrates, cholesterol and fibre than the controls on day 0 and in the 12th month of the study. Fat intake tended to increase over time, but this increase was insufficient to reach the control values. Intake of energy and macronutrients was very similar to that of the controls, both at the beginning and end of the study Significantly lower levels than the controls were only observed in the consumption of saturated fat at baseline, while the proportion of energy provided by macronutrients was higher than in the controls, at the beginning and end of the study (Table 1). Table 2 shows the gender differences between the various variables studied. Comparison of patients and controls shows that the parameters indicative of renal function and plasma Mn were very similar for men and women. Women in the control group had a lower energy and protein consumption than the men. On day 0, the male patients consumed slightly lower quantities of energy and macronutrients than the controls, but the differences were not significant. However, the female patients presented significantly lower consumption levels than their respective controls on day 0. After 12 months, the situation was very similar to what was observed at the beginning of the study regarding the female patients. For the age-related study (Table 3), we examined two age groups (55 years or younger, and over 55 years). This cutoff point was chosen because certain physiological effects of ageing, such as menopause in women and changes in body composition in both genders, begin to appear at this age [19]. The controls aged over 55 years presented higher BMI values than did those aged less than 55 years. On day 0, the older patients also presented higher BMI, but lower mean values of BMI, GFR and plasma uric acid than did the younger patients. All of the parameters indicative of renal function, except for plasma protein, were significantly worse in the younger and older patients than in their respective controls, both at the start and end of the study period. Furthermore, GFR worsened over time in both the younger and the older patients. Our study shows, therefore, that GFR worsens with age and with time. Mn plasma levels at day 0 in the patients were similar in both age groups and significantly higher than in the controls. At 12 months, plasma Mn content
was also higher than in the controls, in both older and younger patients. By the end of the study, circulating Mn had significantly increased in the older patients. These results suggest that, as well as time, greater age is also associated with elevated plasma Mn. Patients aged less than 55 years presented consumption levels similar to their controls, whereas consumption by older patients was significantly lower than that of the controls, except for energy from protein, total fat, polyunsaturated fat and fibre (Table 3). Table 4 presents the results obtained from the patients and controls, adjusted for BMI. Both populations were divided into three groups: normal weight (BMI ≤ 25), overweight (BMI 25.00–29.99), and obese (BMI > 30). When the controls or patients were studied independently, no significant changes were observed between the parameters of renal function and intake due to BMI. However, the comparative study of patients vs. controls for the same BMI group, on day 0 or after 12 months, revealed that the differences found at the beginning were similar to those found at the end of the study. In all three groups (BMI ≤ 25; 25.00–29.99 BMI, and BMI > 30) significant differences were mostly observed in the renal function parameters. Plasma Mn content on day 0 was higher in all groups of patients than in the respective controls. Moreover, Mn levels at the end of the study were higher than in the controls and also higher than those measured at day 0, in all three BMI groups. Table 5 shows the Pearson correlation coefficients obtained between plasma Mn concentration and the variables of renal function, together with the energy and macronutrient intake. Correlations are shown as supplementary data. High positive correlation coefficients were observed between Mn and creatinine and between Mn and plasma urea. However, the positive correlation coefficient between Mn and plasma uric acid was significantly lower. Furthermore, the plasma concentration of Mn presented a strongly negative correlation coefficient with the Cockcroft-Gault index. Table 5 shows that plasma levels of Mn were also negatively correlated, although to a lesser degree, with the intake of energy and macronutrients. Among these parameters, protein intake had the highest correlation coefficient.
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Table 2 BMI, biochemical variables, and energy and macronutrient intake by gender. Patients, N = 64 (Day 0)
Patients, N = 49 (12 months)
Men, N = 33
Controls, N = 62 Women, N = 29
Men, N = 37
Women, N = 27
Men, N = 31
Women, N = 18
BMI (kg/m2 )
26.3 ± 3.9
28.4 ± 5.7
27.8 ± 5.2
29.2 ± 7.8
25.2 ± 3.9
28.7 ± 5.7
Biochemical parameters Plasma creatinine (mg/dL) Cockcroft-Gault index Plasma urea (mg/dL) Plasma uric acid (mg/dL) Plasma total protein (g/dL) Plasma Mn (g/L)
0.79 120 33 5.0 6.7 0.61
± ± ± ± ± ±
0.12 24 6 2.2 0.5 0.20
0.77 110 31 5.1 6.9 0.69
± ± ± ± ± ±
0.11 20 6 2.0 0.6 0.30
3.40 28 111 7.2 7.0 1.99
± ± ± ± ± ±
0.80b 5b 31b 2.0 0.7 0.46b
3.11 22 112 6.9 7.3 1.85
± ± ± ± ± ±
0.94b 5a , b 30b 1.7b 0.5b 0.32b
4.06 26 131 8.1 7.0 2.91
± ± ± ± ± ±
1.44b , c 9b 46b 1.6b 0.6 1.02b , c
3.25 22 120 6.8 7.1 2.88
± ± ± ± ± ±
1.17b 6b 34b 1.1a , b 0.5b 0.53b , c
Energy and macronutrient intakes Energy (MJ/day) Protein (g/day) Energy from protein (%) Total fat (g/day) Energy from total fat (%) Saturated fat (g/day) Monounsaturated fat (g/day) Polyunsaturated fat (g/day) Carbohydrates (g/day) Energy from carbohydrates (%) Cholesterol (mg/day) Fibre (g/day)
11 101 16 113 38 33 55 16 292 43 374 20
± ± ± ± ± ± ± ± ± ± ± ±
4 38 3 61 8 21 27 7 107 7 256 6
8.8 82 16 93 40 26 44 12 232 41 321 17
± ± ± ± ± ± ± ± ± ± ± ±
4a 33a 5 51 8 19 19 6 114 9a 150 11
8.1 81 17 77 36 17 43 11 227 47 280 18
± ± ± ± ± ± ± ± ± ± ± ±
2.0 22 3 27 7 7b 14 3 60 5b 120 6
7.0 65 16 64 38 15 37 8 177 48 233 16
± ± ± ± ± ± ± ± ± ± ± ±
1.4a , b 19a , b 3 20b 7 6b 9b 2b 57a , b 8b 114b 8b
7.7 67 14 76 37 17 42 10 226 50 207 14
± ± ± ± ± ± ± ± ± ± ± ±
1.7 42 5 20 6 12 10 3 41 8b 133 4
7.5 59 13 82 41 16 46 10 211 47 272 16
± ± ± ± ± ± ± ± ± ± ± ±
1.7b 30b 5 23b , c 7 9b 7c 4 52b 8b 182 8
Values are expressed as means ± SD. a Men vs. women. b Patients vs. controls. c Patients at day 0 vs. patients at 12 months. P < 0.05.
Discussion Given the scant information available on the possible role of Mn in CRF, the aim of this study was to investigate changes in plasma Mn levels in predialysis patients with CRF and the relationship with biochemical parameters of clinical interest in monitoring such patients, including energy and macronutrient intake. At the beginning of the study, significant differences between controls and patients were found with respect to the renal function
variables, which is indicative of the presence of altered renal function, and therefore consistent with CRF. The Cockcroft-Gault index reflected a low GFR, and there were high concentrations of plasma creatinine, urea and uric acid (Table 1). Circulating levels of Mn increased significantly over time. By the end of the study, the patients presented Mn levels that were 4.5 times higher than in controls and significantly higher than those found in patients on day 0 (Table 1). Alterations of trace elements in the body fluids and tissues of uraemic patients
Table 3 BMI, biochemical variables, and energy and macronutrient intake by age group. Controls, N = 62
Patients, N = 64 (Day 0)
Patients, N = 49 (12 months)
≤55 years, N = 34
>55 years, N = 28
≤55 years, N = 23
>55 years, N = 41
≤55 years, N = 19
>55 years, N = 30
BMI (kg/m2 )
26.1 ± 4.5
28.5 ± 5.2a
26.0 ± 5.1
29.7 ± 6.7a
25.9 ± 4.9
29.7 ± 6.7a
Biochemical parameters Plasma creatinine (mg/dL) Cockcroft-Gault index Plasma urea (mg/dL) Plasma uric acid (mg/dL) Plasma total protein (g/dL) Plasma Mn (g/L)
0.78 118 32 5.1 7.0 061
± ± ± ± ± ±
0.13 21 6 1.2 0.6 0.20
0.77 112 32 5.0 7.1 0.69
± ± ± ± ± ±
0.11 22 5 1.8 0.6 0.30
3.2 32 111 7.4 6.9 1.92
± ± ± ± ± ±
0.79b 9b 36b 2.2b 0.8 0.43b
3.3 23 112 6.9 7.2 1.91
± ± ± ± ± ±
0.9b 7a ,b 28b 1.7a , b 0.4 0.38b
3.8 28.8 126 7.6 7.0 2.64
± ± ± ± ± ±
1.6b 9.6b 54b 1.8b 0.7 1.11b
3.7 21.4 127 7.7 7.0 3.03
± ± ± ± ± ±
1.7b 6.4a , b 32b 1.4b 0.4 0.71b , c
Energy and macronutrient intakes Energy (Mj/day) 9.8 ± 3.3 Protein (g/day) 93 ± 35 Energy from protein (%) 16 ± 3 Total fat (g/day) 101 ± 42 Energy from total fat (%) 37 ± 8 29 ± 15 Saturated fat (g/day) Monounsaturated fat (g/day) 50 ± 16 15 ± 7 Polyunsaturated fat (g/day) 268 ± 100 Carbohydrates (g/day) Energy from carbohydrates (%) 43 ± 8 Cholesterol (mg/day) 328 ± 175 Fibre (g/day) 19 ± 8
9.9 92 16 106 37 31 54 13 260 41 367 17
± ± ± ± ± ± ± ± ± ± ± ±
4.9 38 5 67 8 24 29 7 125 7 242 9
8.3 83 17 82 37 19 45 12 229 48 294 17
± ± ± ± ± ± ± ± ± ± ± ±
2.0 23 3 29 7 7b 16 3 66 5b 146 4
7.3 70 17 65 36 13 39 9 196 48 242 17
± ± ± ± ± ± ± ± ± ± ± ±
1.8b 21b 2 21b 7 6a, b 8b 2 58b 6b 93b 8
7.5 72 15 78 40 18 42 13 206 47 231 16
± ± ± ± ± ± ± ± ± ± ± ±
2.2b 50 7 22 6 13 9 3 60 8 175 6
7.6 58 13 80 39 17 46 9 225 49 244 14
± ± ± ± ± ± ± ± ± ± ± ±
1.4b 27b 4b , c 22b , c 7 9b 7 4 38b 8b 157b 6
Values are expressed as means ± SD. a ≤50 years vs. >50 years b Patients vs. controls. c Patients at day 0 vs. patients at 12 months. P < 0.05
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Table 4 BMI, biochemical variables, and energy and macronutrient intake by subgroup of BMI (normal weight, overweight and obese). Controls, N= 62
BMI (kg/m2 )
Patients, N = 64 (Day 0)
Patients, N = 49 (12 months)
BMI ≤ 25, N = 22
25 < BMI ≤ 30, N = 22
BMI > 30, N = 18
BMI ≤ 25, N = 20
25 < BMI ≤ 30, N = 23
BMI > 30, N = 21
BMI ≤ 25, N = 17
25 < BMI ≤ 30, N = 19
BMI > 30, N = 13
22.5 ± 1.9
27.3 ± 1.5a
33.8 ± 3.4b , c
22.3 ± 2.2
27.5 ± 1.5a
35.2 ± 5.9b , c
22.4 ± 2.2
27.6 ± 1.4a
35.1 ± 5.9b , c
0.13
0.79 ± 0.12
0.75 ± 0.10
3.0 ± 0.7d
3.5 ± 1.0d
3.3 ± 0.8d
3.6 ± 1.7d
3.6 ± 0.9d
4.0 ± 1.3d
21
117 ± 24
108 ± 22
27 ± 10d
25 ± 8d
28 ± 8d
25 ± 10d
24 ± 7d
23 ± 6d
7
32 ± 5
31 ± 6
105 ± 29d
121 ± 39d
107 ± 16d
117 ± 50d
133 ± 36d
2.4
5.2 ± 2.1
4.8 ± 1.7
7.0 ± 2.2d
7.0 ± 0.7d
7.6 ± 1.3d
7.5 ± 1.7d
7.3 ± 1.9d
7.9 ± 0.7d
0.7
6.8 ± 0.4
6.7 ± 0.5
7.1 ± 0.7
7.0 ± 0.7
7.2 ± 0.4d
7.0 ± 0.7
7.1 ± 0.4
7.1 ± 0.3
0.30
0.63 ± 0.24
0.73 ± 0.24
2.16 ± 0.22d
1.80 ± 0.45d
1.81 ± 0.34d
10.7 ± 5.1
7.2 ± 2.1d
8.2 ± 2.0
7.8 ± 1.6d
7.5 ± 1.6
7.4 ± 1.9
8.0 ± 1.8
100 ± 41 16 ± 3
75 ± 25 17 ± 3
74 ± 24 16 ± 2
78 ± 19 17 ± 3
57 ± 19 13 ± 2d , e
67 ± 21 14 ± 7
65 ± 30 13 ± 6
103 ± 71
68 ± 24
77 ± 33
71 ± 19
78 ± 22
81 ± 20
78 ± 26
35 ± 10
35 ± 6
39 ± 7
37 ± 7
39 ± 6
41 ± 6
37 ± 8
31 ± 23
15 ± 7
17 ± 7
15 ± 7
13 ± 3.7
20 ± 14
18 ± 10
52 ± 25
38 ± 10
44 ± 17
41 ± 8
46 ± 14
44 ± 7
42 ± 12
13 ± 8
10 ± 4
11 ± 3
9±3
11 ± 4
9±1
10 ± 4
299 ± 145
214 ± 63
203 ± 66
214 ± 63d
224 ± 44
200 ± 44
235 ± 49
43 ± 10
49 ± 4
46 ± 7
47 ± 7
51 ± 6
45 ± 6
Biochemical parameters Plasma 0.78 ± creatinine (mg/dL) Cockcroft118 ± Gault index Plasma urea 32 ± (mg/dL) 5.1 ± Plasma uric acid (mg/dL) Plasma total 6.9 ± protein (g/dL) 0.62 ± Plasma Mn (g/L)
Energy and macronutrient intakes Energy 9.1 ± 3.5 9.8 ± 4.2 (Mj/day) 88 ± 33 89 ± 37 Protein (g/day) 17 ± 6 15 ± 3 Energy from protein (%) 95 ± 38 112 ± 63 Total fat (g/day) 39 ± 7 Energy from 41 ± 7 total fat (%) 26 ± 12 33 ± 23 Saturated fat (g/day) 50 ± 15 Monounsaturated 53 ± 25 fat (g/day) 12 ± 7 17 ± 6 Polyunsaturated fat (g/day) 252 ± 97 Carbohydrates 244 ± 100 (g/day) Energy from 41 ± 6 42 ± 8 carbohydrates (%) Cholesterol 308 ± 149 373 ± 181 (mg/day) Fibre (g/day) 19 ± 9 16 ± 7
373 ± 181 20 ± 10
293 ± 160 17 ± 5
d
242 ± 107d 16 ± 2
d
d
250 ± 66 19 ± 9
3.24 ± 1.10d , e
d,e
d
d
223 ± 105 16 ± 6
2.67 ± 0.65d
220 ± 175d 15 ± 7
132 ± 31d , e
2.92 ± 0.88d , e
49 ± 10d
291 ± 111 13 ± 7
Values are means ± SD. a BMI ≤ 25 vs. 25 < BMI ≤ 30. b BMI ≤ 25 vs. BMI > 30. c 25 < BMI ≤ 30 vs. BMI > 30. d Patients vs. controls. e Patients at day 0 vs. patients at 12 months. P < 0.05
depend on many factors (e.g., diet consumption, employment and/or environmental exposure, or degree of malnutrition), but perhaps most important is the degree of kidney failure. The presence of some elements increases in this circumstance (e.g., arsenic, cobalt, caesium, chromium, mercury, molybdenum, silicon and strontium), whereas that of others decreases (e.g., bromine, rubidium, selenium and zinc) [20]. Additionally, the degree of CRF can influence the concentration of a trace element (e.g., bromine is less present in haemodialysis patients, but is found in high concentrations in predialysis patients) [20]. When reviewing this topic, we found some studies involving haemodialysis patients but none referring to circulating Mn levels or to Mn levels in organs in predialysis patients, which limits the discussion of our results. Higher circulating levels of Mn might be due to the gradual tendency for clinical parameters related to CRF to worsen over time. Although the differences found were not statistically significant, a slow progression of CRF was observed (Table 1). In our opinion,
these changes are not related to the type of food consumed and/or environmental exposure because all participants (controls and patients) lived in the same geographical area (province of Granada, Spain). This implies that the cases and controls experienced a similar level of environmental exposure and that the foods they chose were common to the geographical area and therefore very similar. The pharmacological administration of erythropoietin, ferrous sulphate and calcium phosphate may decrease Mn absorption, as low levels of Ca and Fe favour Mn absorption. Moreover, CRF is often accompanied by reduced intestinal Ca absorption, due to insufficient production of calcitriol, leading to hypocalcaemia and decreased production of erythropoietin, which is the main cause of anaemia in uraemic patients. Furthermore, Ca deficiency increases Mn absorption and concentration in the brain [21]. Increased levels of Mn in the blood in adults and children with Fe-deficiency anaemia have also been reported [22,23]. In our study, the following plasma Ca values (mg/dL) were found: 9.9 ± 1.1 (control), 9.6 ± 0.6
C. Sánchez-González et al. / Journal of Trace Elements in Medicine and Biology 31 (2015) 78–84 Table 5 Pearson correlation coefficients between study variables and plasma Mn levels. Plasma Mn (g/L) Plasma creatinine (mg/dL) Cockcroft-Gault index Plasma urea (mg/dL) Plasma uric acid (mg/dL) Energy (Mj/day) Protein (g/day) Total fat (g/day) Carbohydrates (g/day) a
0.748a −0.809a 0.767a 0.431a −0.300a −0.393a −0.266a −0.242a
P < 0.01.
(baseline) and 9.5 ± 0.9 (end of study), and the mean haemoglobin values were (g/dL) 14.3 ± 1.5 (controls), 12.7 ± 1.6 (baseline) and 12.3 ± 1.8 (end of study). Overall, these results indicate the absence of hypocalcaemia and of significant anaemic processes among the patients participating in this study. We conclude, therefore, that the plasma accumulation of Mn is not related to Ca or Fe deficiency. Our finding of increased circulating Mn levels in the patients analysed is consistent with previous studies, which reported increased levels of Mn in uraemic patients undergoing maintenance haemodialysis [6,7]. However, the opposite effect has also been described, with circulating levels of Mn decreasing in such patients [10,14]. These contradictory results might be related to the degree of malnutrition suffered, and over 40% of uraemic patients undergoing maintenance haemodialysis are reported to present protein-energy malnutrition. Malnutrition or the presence of inflammation can lead to low levels of protein in serum, which might explain the low levels of Mn observed in previous studies [24]. Mn is transported in plasma by albumin, globulins and transferrin [2]. In the present study, however, there was no protein-energy malnutrition; the BMI values for the patients indicated overweight, and plasma protein levels were within normal values (Table 1). These circumstances lead us to believe that the higher circulating levels of Mn in the patients were mainly due to CRF. The strongly negative correlation between plasma Mn and the Cockcroft-Gault index, and the positive correlation between Mn and plasma creatinine and urea (Table 5) support our hypothesis that the lower GFR is directly associated with the increased plasma concentration of Mn. In the CRF patients, the intake study revealed lower levels of energy and macronutrient intake compared with the healthy controls (Table 1). Energy intake was below the recommended 35 kcal/kg b.wt./day [25] in both groups (at time 0 and at the end of study). Low energy consumption could predispose an individual to protein malnutrition, as an adequate caloric intake is necessary for nitrogen conservation and protein synthesis. An inverse correlation exists between calorie consumption and the urea generation rate [26,27]. In our study, calories consumed and plasma urea were also correlated (r = −371; P < 0.01). Protein consumption was lower in patients than in controls, at the beginning and at the end of the study, which is in accordance with dietary recommendations for this condition. Patients with CRF are prescribed a hypoproteic diet to reduce uraemic symptoms and to slow disease progression. When the GFR is between 25 and 60 mL/min, a diet that contributes 0.6 g protein/kg weight/day is recommended. This restriction delays the appearance of proteinuria and glomerular fibrosis and also reduces oxidative stress [28]. However, throughout the present study, the patients exceeded the recommended consumption of protein, with approximately 1 g/kg b.wt./day at baseline, decreasing to 0.84 g/kg b.wt./day by the end of the study (Table 1). The latter value indicates that patients followed the recommendations in part and slightly reduced their protein consumption.
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The patients’ fat and carbohydrate consumption at the beginning and end of the study was lower than in the controls, which may be justified by their lower energy consumption. Although the lower consumption of fat affects the three types of fatty acids, a greater repercussion was observed on the consumption of saturated fatty acids, which decreased by approximately 50%, thus producing a better balance between the three types of fat. A better balance of fatty acids, together with reduced cholesterol consumption (below 300 mg/day) (Table 1), may help control the dyslipidemia that is highly prevalent in these patients and can lead to CRF progression [27]. These favourable occurrences result from following the recommended diet. In general, the consumption of carbohydrates and fibre was low, both in controls and in patients. Carbohydrates should account for 50–60% of total energy consumption, but in our study the energy contributed by carbohydrates was clearly below recommended levels. Similar values have been described for the adult population in our geographic area [29]. Nevertheless, we observed a tendency to correct this parameter among patients. The consumption of fibre recommended for CRF patients during predialysis is 20–30 g/day [30], values that are higher than those found in our study. Controlling the consumption of carbohydrates and fibre in CRF is important in order to correct glucose metabolism abnormalities in uraemia [30]. The results obtained did not reflect any significant differences among the study variables because of gender, age or BMI, either in patients or controls. However, some results warrant special attention. In relation to gender, the male patients tended to have higher Mn values than the women. With respect to age, at the end of the study, older patients had a markedly higher concentration of Mn than that at baseline, which was not the case with younger patients. Plasma Mn was little affected by BMI, but normal weight patients had higher levels of Mn than those who were overweight or obese, although the differences were not statistically significant (Tables 2–4). The Cockcroft-Gault index was lower among older patients, both at the beginning and at the end of the study. This indicates that the CRF was more advanced in these patients (Table 2). With respect only to patients (N = 113), increasing age was negatively correlated with the Cockcroft-Gault index (r = −0.516; P < 0.01). However, plasma Mn levels were not affected by gender, age or BMI in patients or controls (Tables 2–4). Conclusions The results obtained in this study show that chronic kidney disease in predialysis patients was associated with increases in the circulating levels of Mn and that these Mn levels increased during the study period. However, further studies are necessary to better determine the possible toxicological effects of Mn on the kidney. Conflict of interest statement None of the authors has any financial conflict of interest to declare. Acknowledgments This research was supported by Plan Nacional I+D project 1FD 1997-0642. We thank Glenn Harding for translating the manuscript into English. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.jtemb.2015.04. 001
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NUTRITION
Association of plasma manganese levels with chronic renal failure Cristina Sánchez-González a , Carlos López-Chaves a , Jorge Gómez-Aracena b , Pilar Galindo c , Pilar Aranda a , Juan Llopis a,∗ a b c
Department of Physiology, Campus Cartuja, University of Granada, E-18071 Granada, Spain Department of Preventive Medicine and Public Health, University of Malaga, E-29071 Malaga, Spain Department of Nephrology, Virgen de las Nieves University Hospital, E-18014 Granada. Spain
a r t i c l e
i n f o
Article history: Received 20 November 2014 Accepted 7 April 2015 Keywords: Manganese Chronic renal failure Gender BMI
a b s t r a c t Manganese (Mn) is an essential trace element involved in the formation of bone and in amino acid, lipid and carbohydrate metabolism. Mn excess may be neurotoxic to humans, affecting specific areas of the central nervous system. However, relatively little is known about its physiological and/or toxicological effects, and very few data are available concerning the role of Mn in chronic renal failure (CRF). This paper describes a 12-month study of the evolution of plasma Mn levels in predialysis patients with CRF and the relationship with energy and macronutrient intake. The participants in this trial were 64 patients with CRF in predialysis and 62 healthy controls. Plasma levels of creatinine, urea, uric acid, total protein and Mn were measured. The glomerular filtration rate (GFR) was calculated using the Cockcroft-Gault index. The CRF patients had higher plasma levels of creatinine, urea, uric acid and Mn and a lower GFR than the controls. Plasma Mn was positively correlated with creatinine, plasma urea and plasma uric acid and was negatively correlated with the GFR and the intake of energy and macronutrients. In conclusion, CRF in predialysis patients is associated with increases in circulating levels of Mn. © 2015 Elsevier GmbH. All rights reserved.
Introduction Alterations in trace element metabolism in renal insufficiency are common. Nevertheless, the mechanisms responsible for these changes are still not fully understood [1,2]. Manganese (Mn) is an essential trace element involved in the formation of bone and in amino acid, lipid and carbohydrate metabolism. However, Mn excess may be neurotoxic to humans, affecting specific areas of the central nervous system [3,4]. Little information exists regarding the behaviour of Mn in renal disease and what has been reported is contradictory and mainly focused on haemodialysis patients. Some authors have observed significant increases in Mn content in the hair of patients [5]. Ohtake et al. [6] reported a case of Mn-induced Parkinsonism in a patient on maintenance haemodialysis therapy. According to another study, the occurrence of bilateral pallidal hyperintensity on T1-weighted images in all patients undergoing haemodialysis is associated with high serum Mn levels [7]. However, other authors have described the opposite effect. Some authors have measured a decrease in Mn
∗ Corresponding author. Tel.: +34 958241000x20320/626797356; fax: +34 958 248959. E-mail address: [email protected] (J. Llopis). http://dx.doi.org/10.1016/j.jtemb.2015.04.001 0946-672X/© 2015 Elsevier GmbH. All rights reserved.
levels in haemodialysis patients [8–10]. Koh et al. [11] observed an association between low Mn values in blood and the risk of renal disease, and suggested that this situation may favour disease progression. This element is a cofactor for SOD, so Mn deficiency may contribute to excess oxidative stress in uraemia [12–14]. Given the limited information available on the role of Mn in chronic renal failure (CRF), the aim of this study is to investigate changes in plasma levels of Mn in predialysis patients with CRF and their relation to the biochemical parameters used in monitoring these patients and to the intake of energy and macronutrients.
Materials and methods Patients The participants in this cross-sectional trial were patients with CRF in predialysis who attended the nephrology outpatient clinic of the Virgen de las Nieves University Hospital, Granada (Spain). The following inclusion criteria were applied: plasma creatinine concentration >2.5 mg/dL, plasma creatinine clearance between 10 and 45 mL/min, stable clinical condition (stable blood pressure; no special diet; no digestive system or systemic disease, neoplasias or treatment with corticosteroids or immunosuppressors), normalised metabolic acidosis and lipid alterations, age between 18
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and 70 years. This study was carried out in accordance with the World Medical Association Code of Ethics (Declaration of Helsinki) and all procedures were approved by the Hospital’s Ethics Committee. The study group comprised 64 patients (27 women, 37 men) aged 18–70 years with a mean age of 54 ± 16 years (mean ± SD). Control samples were obtained at random from adults aged 18–70 years living in Granada (Spain). Control participants were asked whether they had any acute or chronic illness and were included if they were (or appeared to be) in good health; pregnant and lactating subjects were excluded. The controls included 62 healthy people (33 men and 29 women) with a mean age of 46 ± 10 years. All participants provided their consent by signing an informed consent form. On day 0, all participants, and at the end of the study, only patients received a physical examination and clinical as well as nutritional data were recorded. The experimental phase of our study lasted 12 months, during which period the patients consumed the low-protein diets recommended by the hospital. Patients aged younger than 60 years and non-obese patients consumed a diet that provided 35 kcal/kg b.wt./day. Patients with obesity and/or older than 60 years were advised to consume a diet that provided 30 kcal/kg b.wt./day. To adjust the energy content of the low-protein diet, we considered obesity to exist when the participant weighed more than 125% of ideal weight [15]. After 12 months, the participation rate was 76.5%. The reasons for dropout or withdrawal included scheduled dialysis, death, laboratory error or loss of samples. The pharmacological treatment was similar for all patients and was adjusted depending on the individual’s clinical status. Medications included calcium-chelated phosphate, calcitriol, oral sodium bicarbonate, ferrous sulphate, antihypertensives (mainly angiotensin-converting enzyme inhibitors), furosemide and subcutaneous erythropoietin. At the beginning of the study and after 12 months, food consumption was assessed by a 24-h recall method that was repeated over 3 days (including a weekend or holiday) [16]. Data were obtained by a dietician with the aid of an open questionnaire and photographs as a reference for portion size. The pictures displayed fresh foods or foods prepared according to standard recipes for dishes that are widely consumed in the study area. Food intake was converted to energy and nutrients using the Spanish Food Composition Table [17]. The food composition database utilised AYS44 diet analysis software obtained from ASDE, SA (Valencia, Spain). Body weight was measured with a portable digital scale (Tefal, Sensitive Computer 9202 series 2/0, France) with a precision of 0.1 kg, and height was measured with a portable stadiometer (Holtain Portable, London, UK) with a precision of 0.1 cm. All measurements were obtained following the techniques and recommendations of the International Biological Programme by personnel suitably trained for this task. Analytical methods In the morning, blood was collected (10 mL) during fasting conditions in tubes that contained lithium heparin as an anticoagulant (Venoject, Terumo Corporation, Leuven, Belgium). The samples were centrifuged at 1200 × g for 15 min at 20 ◦ C to separate the plasma and were stored at −80 ◦ C until analysis. Excreted urine over a 24-h period was collected, following standard guidelines. Diuresis was measured and an aliquot stored at −80 ◦ C until analysis. Creatinine in plasma and 24-h urine, as well as the urea, uric acid and total protein concentrations in plasma were measured with enzymatic colorimetric tests in a Hitachi Modular P autoanalyser (Roche Diagnostics, Grenzach, Germany). The glomerular filtration rate (GFR) was estimated in patients by creatinine clearance
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and by the determination of diuresis and plasma and urinary creatinine at 24 h. The GFR was also measured in the patients and controls using the Cockcroft-Gault index = (140 − age/72 × plasma creatinine) × weight (×0.85 for women) [18]. Plasma Mn was determined using an inductively coupled plasma mass spectrometer (ICP-MS) model 7500 supplied by Agilent Technologies (Agilent, Tokyo, Japan), using a carrier gas flow of 1.03 L/min, collision gas (He) flow of 4.3 mL/min, RF power of 1550 W and energy discrimination of 3 V. All lenses were optimised daily. All materials used in the analysis were previously cleaned with supra-pure nitric acid and ultra-pure water (18.2 ) obtained using a Milli Q system. Samples and the certified reference material (Seronorm Trace Elements Serum L-1, Ref 201405. Billingstad, Norway) were prepared by attack with nitric acid and hydrogen peroxide (supra-pure quality, Merck) in a microwave digester (Milestone, Sorisole, Italy). When the samples had been digested, the extracts were collected and made up to a final volume of 10 mL with-ultra pure water for subsequent analysis. The calibration curve was prepared following the Ga addition technique (adding 0.04 mg/L) as an internal standard, using stock solutions of 1000 mg/L of Mn (Merck). The accuracy of the method was evaluated by analysis of the certified reference material, obtaining the value of 8.2 ± 0.2 g/L (certified value 7.8–8.8 g/L), and by recovery studies in samples of organs enriched with Mn standards, obtaining a recovery of 93%. The mean of five separate determinations was used. Statistical analysis All variables and indexes were analysed by descriptive statistics. Results are reported as means and standard deviations. When the data were distributed normally according to the Kolmogorov–Smirnov test, parametric tests (Student’s t-test for independent or related samples) were used. For variables that required nonparametric testing, the Mann–Whitney test for unrelated samples was used. Linear regression analysis was used to obtain bivariate correlations. Pearson’s correlation coefficient was calculated for the 95% confidence levels. All analyses were conducted with version 15.0 of the Statistical Package for Social Sciences (SPSS Inc., Chicago, IL). Differences were considered significant at the 5% probability level. Results This paper examines the 12-month evolution of plasma Mn levels in predialysis patients with CRF and the relationship with energy and macronutrient intake. Table 1 lists the following characteristics of the participants, showing mean values and SD for controls and patients at day 0 and for patients after 12 months: age, anthropometric variables (weight, height, body mass index [BMI]), plasma parameters indicative of renal function (plasma creatinine, Cockcroft-Gault index, plasma urea, plasma uric acid and plasma total proteins), plasma Mn and energy and macronutrient intake. All these parameters, except total plasma proteins, worsened significantly in the patients compared to controls during the study period, which is indicative of progressive renal dysfunction. Interestingly, patients with CRF had higher plasma Mn levels than the controls at the beginning of the study and these concentrations had increased significantly by the end of the study. In this study, we also evaluated the relationship between plasma levels of Mn and macronutrient consumption. This relationship had not been studied previously due to the unreliability of the food composition tables, as the number of foods in which Mn is present is very low. In our study, the female patients had a lower consumption
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Table 1 Characteristics of the participants. Controls, N = 62 Age (years) Weight (kg) BMI (kg/m2 )
46 ± 10 73 ± 13 27 ± 3
Biochemical parameters Plasma creatinine (mg/dL) Glomerular filtration rate (mL/min/1.73 m2 ) Cockcroft-Gault index Plasma urea (mg/dL) Plasma uric acid (mg/dL) Plasma total protein (g/dL) Plasma Mn (g/L)
0.68 ± – 116 ± 30 ± 4.8 ± 6.8 ± 0.65 ±
0.11
Energy and macronutrient intakes Energy (Mj/day) Protein (g/day) Energy from protein (%) Total fat (g/day) Energy from total fat (%) Saturated fat (g/day) Monounsaturated fat (g/day) Polyunsaturated fat (g/day) Carbohydrates (g/day) Energy from carbohydrates (%) Cholesterol (mg/day) Fibre (g/day)
10 92 16 104 39 30 52 14 264 42 349 18
± ± ± ± ± ± ± ± ± ± ± ±
Patients, N = 64 (Day 0) 54 ± 16a 76 ± 16 28 ± 6
Patients, N = 49 (12 months) 55 ± 16a 75 ± 16 27 ± 6
22 5 2.1 0.6 0.26
3.1 27 26 111 7.0 7.0 1.92
± ± ± ± ± ± ±
0.8a 9 9a 31a 1.9a 0.3 0.40a
3.7 25 24 123 7.5 7.2 2.90
± ± ± ± ± ± ±
1.0a 14 8a 41a 1.6a 0.5 0.86a , b
4 36 4 57 8 20 24 7 113 8 213 9
7.5 75 17 72 37 16 41 10 209 48 263 17
± ± ± ± ± ± ± ± ± ± ± ±
2a 22a 3 26a 7 7a 13a 3 63a 6a 119a 8
7.7 63 13 79 39 17 44 10 218 48 240 15
± ± ± ± ± ± ± ± ± ± ± ±
2a 14a 5a , b 21a 7 10a 12 6 46 8 160a 6
Values are expressed as the means ± SD. a Patients vs. controls. b Patients at day 0 vs. patients at 12 months. P < 0.05.
of energy, protein, fat, carbohydrates, cholesterol and fibre than the controls on day 0 and in the 12th month of the study. Fat intake tended to increase over time, but this increase was insufficient to reach the control values. Intake of energy and macronutrients was very similar to that of the controls, both at the beginning and end of the study Significantly lower levels than the controls were only observed in the consumption of saturated fat at baseline, while the proportion of energy provided by macronutrients was higher than in the controls, at the beginning and end of the study (Table 1). Table 2 shows the gender differences between the various variables studied. Comparison of patients and controls shows that the parameters indicative of renal function and plasma Mn were very similar for men and women. Women in the control group had a lower energy and protein consumption than the men. On day 0, the male patients consumed slightly lower quantities of energy and macronutrients than the controls, but the differences were not significant. However, the female patients presented significantly lower consumption levels than their respective controls on day 0. After 12 months, the situation was very similar to what was observed at the beginning of the study regarding the female patients. For the age-related study (Table 3), we examined two age groups (55 years or younger, and over 55 years). This cutoff point was chosen because certain physiological effects of ageing, such as menopause in women and changes in body composition in both genders, begin to appear at this age [19]. The controls aged over 55 years presented higher BMI values than did those aged less than 55 years. On day 0, the older patients also presented higher BMI, but lower mean values of BMI, GFR and plasma uric acid than did the younger patients. All of the parameters indicative of renal function, except for plasma protein, were significantly worse in the younger and older patients than in their respective controls, both at the start and end of the study period. Furthermore, GFR worsened over time in both the younger and the older patients. Our study shows, therefore, that GFR worsens with age and with time. Mn plasma levels at day 0 in the patients were similar in both age groups and significantly higher than in the controls. At 12 months, plasma Mn content
was also higher than in the controls, in both older and younger patients. By the end of the study, circulating Mn had significantly increased in the older patients. These results suggest that, as well as time, greater age is also associated with elevated plasma Mn. Patients aged less than 55 years presented consumption levels similar to their controls, whereas consumption by older patients was significantly lower than that of the controls, except for energy from protein, total fat, polyunsaturated fat and fibre (Table 3). Table 4 presents the results obtained from the patients and controls, adjusted for BMI. Both populations were divided into three groups: normal weight (BMI ≤ 25), overweight (BMI 25.00–29.99), and obese (BMI > 30). When the controls or patients were studied independently, no significant changes were observed between the parameters of renal function and intake due to BMI. However, the comparative study of patients vs. controls for the same BMI group, on day 0 or after 12 months, revealed that the differences found at the beginning were similar to those found at the end of the study. In all three groups (BMI ≤ 25; 25.00–29.99 BMI, and BMI > 30) significant differences were mostly observed in the renal function parameters. Plasma Mn content on day 0 was higher in all groups of patients than in the respective controls. Moreover, Mn levels at the end of the study were higher than in the controls and also higher than those measured at day 0, in all three BMI groups. Table 5 shows the Pearson correlation coefficients obtained between plasma Mn concentration and the variables of renal function, together with the energy and macronutrient intake. Correlations are shown as supplementary data. High positive correlation coefficients were observed between Mn and creatinine and between Mn and plasma urea. However, the positive correlation coefficient between Mn and plasma uric acid was significantly lower. Furthermore, the plasma concentration of Mn presented a strongly negative correlation coefficient with the Cockcroft-Gault index. Table 5 shows that plasma levels of Mn were also negatively correlated, although to a lesser degree, with the intake of energy and macronutrients. Among these parameters, protein intake had the highest correlation coefficient.
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Table 2 BMI, biochemical variables, and energy and macronutrient intake by gender. Patients, N = 64 (Day 0)
Patients, N = 49 (12 months)
Men, N = 33
Controls, N = 62 Women, N = 29
Men, N = 37
Women, N = 27
Men, N = 31
Women, N = 18
BMI (kg/m2 )
26.3 ± 3.9
28.4 ± 5.7
27.8 ± 5.2
29.2 ± 7.8
25.2 ± 3.9
28.7 ± 5.7
Biochemical parameters Plasma creatinine (mg/dL) Cockcroft-Gault index Plasma urea (mg/dL) Plasma uric acid (mg/dL) Plasma total protein (g/dL) Plasma Mn (g/L)
0.79 120 33 5.0 6.7 0.61
± ± ± ± ± ±
0.12 24 6 2.2 0.5 0.20
0.77 110 31 5.1 6.9 0.69
± ± ± ± ± ±
0.11 20 6 2.0 0.6 0.30
3.40 28 111 7.2 7.0 1.99
± ± ± ± ± ±
0.80b 5b 31b 2.0 0.7 0.46b
3.11 22 112 6.9 7.3 1.85
± ± ± ± ± ±
0.94b 5a , b 30b 1.7b 0.5b 0.32b
4.06 26 131 8.1 7.0 2.91
± ± ± ± ± ±
1.44b , c 9b 46b 1.6b 0.6 1.02b , c
3.25 22 120 6.8 7.1 2.88
± ± ± ± ± ±
1.17b 6b 34b 1.1a , b 0.5b 0.53b , c
Energy and macronutrient intakes Energy (MJ/day) Protein (g/day) Energy from protein (%) Total fat (g/day) Energy from total fat (%) Saturated fat (g/day) Monounsaturated fat (g/day) Polyunsaturated fat (g/day) Carbohydrates (g/day) Energy from carbohydrates (%) Cholesterol (mg/day) Fibre (g/day)
11 101 16 113 38 33 55 16 292 43 374 20
± ± ± ± ± ± ± ± ± ± ± ±
4 38 3 61 8 21 27 7 107 7 256 6
8.8 82 16 93 40 26 44 12 232 41 321 17
± ± ± ± ± ± ± ± ± ± ± ±
4a 33a 5 51 8 19 19 6 114 9a 150 11
8.1 81 17 77 36 17 43 11 227 47 280 18
± ± ± ± ± ± ± ± ± ± ± ±
2.0 22 3 27 7 7b 14 3 60 5b 120 6
7.0 65 16 64 38 15 37 8 177 48 233 16
± ± ± ± ± ± ± ± ± ± ± ±
1.4a , b 19a , b 3 20b 7 6b 9b 2b 57a , b 8b 114b 8b
7.7 67 14 76 37 17 42 10 226 50 207 14
± ± ± ± ± ± ± ± ± ± ± ±
1.7 42 5 20 6 12 10 3 41 8b 133 4
7.5 59 13 82 41 16 46 10 211 47 272 16
± ± ± ± ± ± ± ± ± ± ± ±
1.7b 30b 5 23b , c 7 9b 7c 4 52b 8b 182 8
Values are expressed as means ± SD. a Men vs. women. b Patients vs. controls. c Patients at day 0 vs. patients at 12 months. P < 0.05.
Discussion Given the scant information available on the possible role of Mn in CRF, the aim of this study was to investigate changes in plasma Mn levels in predialysis patients with CRF and the relationship with biochemical parameters of clinical interest in monitoring such patients, including energy and macronutrient intake. At the beginning of the study, significant differences between controls and patients were found with respect to the renal function
variables, which is indicative of the presence of altered renal function, and therefore consistent with CRF. The Cockcroft-Gault index reflected a low GFR, and there were high concentrations of plasma creatinine, urea and uric acid (Table 1). Circulating levels of Mn increased significantly over time. By the end of the study, the patients presented Mn levels that were 4.5 times higher than in controls and significantly higher than those found in patients on day 0 (Table 1). Alterations of trace elements in the body fluids and tissues of uraemic patients
Table 3 BMI, biochemical variables, and energy and macronutrient intake by age group. Controls, N = 62
Patients, N = 64 (Day 0)
Patients, N = 49 (12 months)
≤55 years, N = 34
>55 years, N = 28
≤55 years, N = 23
>55 years, N = 41
≤55 years, N = 19
>55 years, N = 30
BMI (kg/m2 )
26.1 ± 4.5
28.5 ± 5.2a
26.0 ± 5.1
29.7 ± 6.7a
25.9 ± 4.9
29.7 ± 6.7a
Biochemical parameters Plasma creatinine (mg/dL) Cockcroft-Gault index Plasma urea (mg/dL) Plasma uric acid (mg/dL) Plasma total protein (g/dL) Plasma Mn (g/L)
0.78 118 32 5.1 7.0 061
± ± ± ± ± ±
0.13 21 6 1.2 0.6 0.20
0.77 112 32 5.0 7.1 0.69
± ± ± ± ± ±
0.11 22 5 1.8 0.6 0.30
3.2 32 111 7.4 6.9 1.92
± ± ± ± ± ±
0.79b 9b 36b 2.2b 0.8 0.43b
3.3 23 112 6.9 7.2 1.91
± ± ± ± ± ±
0.9b 7a ,b 28b 1.7a , b 0.4 0.38b
3.8 28.8 126 7.6 7.0 2.64
± ± ± ± ± ±
1.6b 9.6b 54b 1.8b 0.7 1.11b
3.7 21.4 127 7.7 7.0 3.03
± ± ± ± ± ±
1.7b 6.4a , b 32b 1.4b 0.4 0.71b , c
Energy and macronutrient intakes Energy (Mj/day) 9.8 ± 3.3 Protein (g/day) 93 ± 35 Energy from protein (%) 16 ± 3 Total fat (g/day) 101 ± 42 Energy from total fat (%) 37 ± 8 29 ± 15 Saturated fat (g/day) Monounsaturated fat (g/day) 50 ± 16 15 ± 7 Polyunsaturated fat (g/day) 268 ± 100 Carbohydrates (g/day) Energy from carbohydrates (%) 43 ± 8 Cholesterol (mg/day) 328 ± 175 Fibre (g/day) 19 ± 8
9.9 92 16 106 37 31 54 13 260 41 367 17
± ± ± ± ± ± ± ± ± ± ± ±
4.9 38 5 67 8 24 29 7 125 7 242 9
8.3 83 17 82 37 19 45 12 229 48 294 17
± ± ± ± ± ± ± ± ± ± ± ±
2.0 23 3 29 7 7b 16 3 66 5b 146 4
7.3 70 17 65 36 13 39 9 196 48 242 17
± ± ± ± ± ± ± ± ± ± ± ±
1.8b 21b 2 21b 7 6a, b 8b 2 58b 6b 93b 8
7.5 72 15 78 40 18 42 13 206 47 231 16
± ± ± ± ± ± ± ± ± ± ± ±
2.2b 50 7 22 6 13 9 3 60 8 175 6
7.6 58 13 80 39 17 46 9 225 49 244 14
± ± ± ± ± ± ± ± ± ± ± ±
1.4b 27b 4b , c 22b , c 7 9b 7 4 38b 8b 157b 6
Values are expressed as means ± SD. a ≤50 years vs. >50 years b Patients vs. controls. c Patients at day 0 vs. patients at 12 months. P < 0.05
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Table 4 BMI, biochemical variables, and energy and macronutrient intake by subgroup of BMI (normal weight, overweight and obese). Controls, N= 62
BMI (kg/m2 )
Patients, N = 64 (Day 0)
Patients, N = 49 (12 months)
BMI ≤ 25, N = 22
25 < BMI ≤ 30, N = 22
BMI > 30, N = 18
BMI ≤ 25, N = 20
25 < BMI ≤ 30, N = 23
BMI > 30, N = 21
BMI ≤ 25, N = 17
25 < BMI ≤ 30, N = 19
BMI > 30, N = 13
22.5 ± 1.9
27.3 ± 1.5a
33.8 ± 3.4b , c
22.3 ± 2.2
27.5 ± 1.5a
35.2 ± 5.9b , c
22.4 ± 2.2
27.6 ± 1.4a
35.1 ± 5.9b , c
0.13
0.79 ± 0.12
0.75 ± 0.10
3.0 ± 0.7d
3.5 ± 1.0d
3.3 ± 0.8d
3.6 ± 1.7d
3.6 ± 0.9d
4.0 ± 1.3d
21
117 ± 24
108 ± 22
27 ± 10d
25 ± 8d
28 ± 8d
25 ± 10d
24 ± 7d
23 ± 6d
7
32 ± 5
31 ± 6
105 ± 29d
121 ± 39d
107 ± 16d
117 ± 50d
133 ± 36d
2.4
5.2 ± 2.1
4.8 ± 1.7
7.0 ± 2.2d
7.0 ± 0.7d
7.6 ± 1.3d
7.5 ± 1.7d
7.3 ± 1.9d
7.9 ± 0.7d
0.7
6.8 ± 0.4
6.7 ± 0.5
7.1 ± 0.7
7.0 ± 0.7
7.2 ± 0.4d
7.0 ± 0.7
7.1 ± 0.4
7.1 ± 0.3
0.30
0.63 ± 0.24
0.73 ± 0.24
2.16 ± 0.22d
1.80 ± 0.45d
1.81 ± 0.34d
10.7 ± 5.1
7.2 ± 2.1d
8.2 ± 2.0
7.8 ± 1.6d
7.5 ± 1.6
7.4 ± 1.9
8.0 ± 1.8
100 ± 41 16 ± 3
75 ± 25 17 ± 3
74 ± 24 16 ± 2
78 ± 19 17 ± 3
57 ± 19 13 ± 2d , e
67 ± 21 14 ± 7
65 ± 30 13 ± 6
103 ± 71
68 ± 24
77 ± 33
71 ± 19
78 ± 22
81 ± 20
78 ± 26
35 ± 10
35 ± 6
39 ± 7
37 ± 7
39 ± 6
41 ± 6
37 ± 8
31 ± 23
15 ± 7
17 ± 7
15 ± 7
13 ± 3.7
20 ± 14
18 ± 10
52 ± 25
38 ± 10
44 ± 17
41 ± 8
46 ± 14
44 ± 7
42 ± 12
13 ± 8
10 ± 4
11 ± 3
9±3
11 ± 4
9±1
10 ± 4
299 ± 145
214 ± 63
203 ± 66
214 ± 63d
224 ± 44
200 ± 44
235 ± 49
43 ± 10
49 ± 4
46 ± 7
47 ± 7
51 ± 6
45 ± 6
Biochemical parameters Plasma 0.78 ± creatinine (mg/dL) Cockcroft118 ± Gault index Plasma urea 32 ± (mg/dL) 5.1 ± Plasma uric acid (mg/dL) Plasma total 6.9 ± protein (g/dL) 0.62 ± Plasma Mn (g/L)
Energy and macronutrient intakes Energy 9.1 ± 3.5 9.8 ± 4.2 (Mj/day) 88 ± 33 89 ± 37 Protein (g/day) 17 ± 6 15 ± 3 Energy from protein (%) 95 ± 38 112 ± 63 Total fat (g/day) 39 ± 7 Energy from 41 ± 7 total fat (%) 26 ± 12 33 ± 23 Saturated fat (g/day) 50 ± 15 Monounsaturated 53 ± 25 fat (g/day) 12 ± 7 17 ± 6 Polyunsaturated fat (g/day) 252 ± 97 Carbohydrates 244 ± 100 (g/day) Energy from 41 ± 6 42 ± 8 carbohydrates (%) Cholesterol 308 ± 149 373 ± 181 (mg/day) Fibre (g/day) 19 ± 9 16 ± 7
373 ± 181 20 ± 10
293 ± 160 17 ± 5
d
242 ± 107d 16 ± 2
d
d
250 ± 66 19 ± 9
3.24 ± 1.10d , e
d,e
d
d
223 ± 105 16 ± 6
2.67 ± 0.65d
220 ± 175d 15 ± 7
132 ± 31d , e
2.92 ± 0.88d , e
49 ± 10d
291 ± 111 13 ± 7
Values are means ± SD. a BMI ≤ 25 vs. 25 < BMI ≤ 30. b BMI ≤ 25 vs. BMI > 30. c 25 < BMI ≤ 30 vs. BMI > 30. d Patients vs. controls. e Patients at day 0 vs. patients at 12 months. P < 0.05
depend on many factors (e.g., diet consumption, employment and/or environmental exposure, or degree of malnutrition), but perhaps most important is the degree of kidney failure. The presence of some elements increases in this circumstance (e.g., arsenic, cobalt, caesium, chromium, mercury, molybdenum, silicon and strontium), whereas that of others decreases (e.g., bromine, rubidium, selenium and zinc) [20]. Additionally, the degree of CRF can influence the concentration of a trace element (e.g., bromine is less present in haemodialysis patients, but is found in high concentrations in predialysis patients) [20]. When reviewing this topic, we found some studies involving haemodialysis patients but none referring to circulating Mn levels or to Mn levels in organs in predialysis patients, which limits the discussion of our results. Higher circulating levels of Mn might be due to the gradual tendency for clinical parameters related to CRF to worsen over time. Although the differences found were not statistically significant, a slow progression of CRF was observed (Table 1). In our opinion,
these changes are not related to the type of food consumed and/or environmental exposure because all participants (controls and patients) lived in the same geographical area (province of Granada, Spain). This implies that the cases and controls experienced a similar level of environmental exposure and that the foods they chose were common to the geographical area and therefore very similar. The pharmacological administration of erythropoietin, ferrous sulphate and calcium phosphate may decrease Mn absorption, as low levels of Ca and Fe favour Mn absorption. Moreover, CRF is often accompanied by reduced intestinal Ca absorption, due to insufficient production of calcitriol, leading to hypocalcaemia and decreased production of erythropoietin, which is the main cause of anaemia in uraemic patients. Furthermore, Ca deficiency increases Mn absorption and concentration in the brain [21]. Increased levels of Mn in the blood in adults and children with Fe-deficiency anaemia have also been reported [22,23]. In our study, the following plasma Ca values (mg/dL) were found: 9.9 ± 1.1 (control), 9.6 ± 0.6
C. Sánchez-González et al. / Journal of Trace Elements in Medicine and Biology 31 (2015) 78–84 Table 5 Pearson correlation coefficients between study variables and plasma Mn levels. Plasma Mn (g/L) Plasma creatinine (mg/dL) Cockcroft-Gault index Plasma urea (mg/dL) Plasma uric acid (mg/dL) Energy (Mj/day) Protein (g/day) Total fat (g/day) Carbohydrates (g/day) a
0.748a −0.809a 0.767a 0.431a −0.300a −0.393a −0.266a −0.242a
P < 0.01.
(baseline) and 9.5 ± 0.9 (end of study), and the mean haemoglobin values were (g/dL) 14.3 ± 1.5 (controls), 12.7 ± 1.6 (baseline) and 12.3 ± 1.8 (end of study). Overall, these results indicate the absence of hypocalcaemia and of significant anaemic processes among the patients participating in this study. We conclude, therefore, that the plasma accumulation of Mn is not related to Ca or Fe deficiency. Our finding of increased circulating Mn levels in the patients analysed is consistent with previous studies, which reported increased levels of Mn in uraemic patients undergoing maintenance haemodialysis [6,7]. However, the opposite effect has also been described, with circulating levels of Mn decreasing in such patients [10,14]. These contradictory results might be related to the degree of malnutrition suffered, and over 40% of uraemic patients undergoing maintenance haemodialysis are reported to present protein-energy malnutrition. Malnutrition or the presence of inflammation can lead to low levels of protein in serum, which might explain the low levels of Mn observed in previous studies [24]. Mn is transported in plasma by albumin, globulins and transferrin [2]. In the present study, however, there was no protein-energy malnutrition; the BMI values for the patients indicated overweight, and plasma protein levels were within normal values (Table 1). These circumstances lead us to believe that the higher circulating levels of Mn in the patients were mainly due to CRF. The strongly negative correlation between plasma Mn and the Cockcroft-Gault index, and the positive correlation between Mn and plasma creatinine and urea (Table 5) support our hypothesis that the lower GFR is directly associated with the increased plasma concentration of Mn. In the CRF patients, the intake study revealed lower levels of energy and macronutrient intake compared with the healthy controls (Table 1). Energy intake was below the recommended 35 kcal/kg b.wt./day [25] in both groups (at time 0 and at the end of study). Low energy consumption could predispose an individual to protein malnutrition, as an adequate caloric intake is necessary for nitrogen conservation and protein synthesis. An inverse correlation exists between calorie consumption and the urea generation rate [26,27]. In our study, calories consumed and plasma urea were also correlated (r = −371; P < 0.01). Protein consumption was lower in patients than in controls, at the beginning and at the end of the study, which is in accordance with dietary recommendations for this condition. Patients with CRF are prescribed a hypoproteic diet to reduce uraemic symptoms and to slow disease progression. When the GFR is between 25 and 60 mL/min, a diet that contributes 0.6 g protein/kg weight/day is recommended. This restriction delays the appearance of proteinuria and glomerular fibrosis and also reduces oxidative stress [28]. However, throughout the present study, the patients exceeded the recommended consumption of protein, with approximately 1 g/kg b.wt./day at baseline, decreasing to 0.84 g/kg b.wt./day by the end of the study (Table 1). The latter value indicates that patients followed the recommendations in part and slightly reduced their protein consumption.
83
The patients’ fat and carbohydrate consumption at the beginning and end of the study was lower than in the controls, which may be justified by their lower energy consumption. Although the lower consumption of fat affects the three types of fatty acids, a greater repercussion was observed on the consumption of saturated fatty acids, which decreased by approximately 50%, thus producing a better balance between the three types of fat. A better balance of fatty acids, together with reduced cholesterol consumption (below 300 mg/day) (Table 1), may help control the dyslipidemia that is highly prevalent in these patients and can lead to CRF progression [27]. These favourable occurrences result from following the recommended diet. In general, the consumption of carbohydrates and fibre was low, both in controls and in patients. Carbohydrates should account for 50–60% of total energy consumption, but in our study the energy contributed by carbohydrates was clearly below recommended levels. Similar values have been described for the adult population in our geographic area [29]. Nevertheless, we observed a tendency to correct this parameter among patients. The consumption of fibre recommended for CRF patients during predialysis is 20–30 g/day [30], values that are higher than those found in our study. Controlling the consumption of carbohydrates and fibre in CRF is important in order to correct glucose metabolism abnormalities in uraemia [30]. The results obtained did not reflect any significant differences among the study variables because of gender, age or BMI, either in patients or controls. However, some results warrant special attention. In relation to gender, the male patients tended to have higher Mn values than the women. With respect to age, at the end of the study, older patients had a markedly higher concentration of Mn than that at baseline, which was not the case with younger patients. Plasma Mn was little affected by BMI, but normal weight patients had higher levels of Mn than those who were overweight or obese, although the differences were not statistically significant (Tables 2–4). The Cockcroft-Gault index was lower among older patients, both at the beginning and at the end of the study. This indicates that the CRF was more advanced in these patients (Table 2). With respect only to patients (N = 113), increasing age was negatively correlated with the Cockcroft-Gault index (r = −0.516; P < 0.01). However, plasma Mn levels were not affected by gender, age or BMI in patients or controls (Tables 2–4). Conclusions The results obtained in this study show that chronic kidney disease in predialysis patients was associated with increases in the circulating levels of Mn and that these Mn levels increased during the study period. However, further studies are necessary to better determine the possible toxicological effects of Mn on the kidney. Conflict of interest statement None of the authors has any financial conflict of interest to declare. Acknowledgments This research was supported by Plan Nacional I+D project 1FD 1997-0642. We thank Glenn Harding for translating the manuscript into English. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.jtemb.2015.04. 001
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